pth <- "X:/wissenschaftliche Veröffentlichungen/Publikationen/2022/Proteomics_JRS_DL/data/ta_yeast/results/"
filelist = list.files(path = pth, pattern = ".*.RDS")
for (file in filelist[grep("Razor",filelist)][-c(1,2)]){
tmp <- readRDS(paste(pth,file,sep=""))
tmp <- tmp[[1]]
dat <- tmp
yeasx <- grep("YEASX",dat$FASTA)
wheat <- grep("WHEAT",dat$FASTA)
# write human oder trica in a column
for (i in 1:nrow(dat)){
if (grepl("YEASX",dat$FASTA[i])){
dat$org[i] <- "YEASX"
}
else if (grepl("WHEAT",dat$FASTA[i])){
dat$org[i] <- "WHEAT"
}
else {
dat$org[i] <- NA
}
}
dat$org[intersect(yeasx,wheat)] <- "YEASX/WHEAT"
dat4plot <- dat[,-c(ncol(dat)-1)]
dat4plot_long <- melt(dat4plot, id = c("org"))
tmp <- regmatches(dat4plot_long$variable,gregexpr("(?<=des.).*",dat4plot_long$variable,perl=TRUE))
tmp <- unlist(tmp)
dat4plot_long$variable <- tmp
p <- ggplot(data=dat4plot_long, aes(x=variable, y=as.numeric(value), fill=org)) +
stat_summary(fun.y = sum, geom = "bar", position = "dodge") +
xlab("sample name") +
ylab("counts") +
theme(axis.text.x = element_text(angle = 90)) +
labs(title = file)
cat("\n")
#cat(knit_print(ggplotly(p)))
cat("##"," ",file,"\n")
print(htmltools::tagList(ggplotly(p)))
cat("\n")
if (print_fasta==TRUE){
for (i in 1:(ncol(dat)-2)){
cat("\n")
text <- paste(" Fasta Headers - Sample",unique(dat4plot_long$variable)[i])
cat("###",text,"\n")
cat("\"n")
print(dat$FASTA[which(dat[,i])])
}
}
}\[%WHEAT/YEAST={number of proteins wheat/yeast} / {number of proteins tribolium}\]
# compare TC - ta/wheat
res_TC <- c(
"results_run1_mqpar_extracts_2gether_E3_D1_combined_txt_proteinGroups.txt_summary.csv",
"results_run1_mqpar_extracts_2gether_E4_D1_a-j_combined_txt_proteinGroups.txt_summary.csv",
"results_run1_mqpar_extracts_2gether_D2_combined_txt_proteinGroups.txt_summary.csv",
"results_run1_mqpar_extracts_2gether_E4_D1_B_combined_txt_proteinGroups.txt_summary.csv",
"results_run1_mqpar_extracts_2gether_E4_D1_AF_TF_combined_txt_proteinGroups.txt_summary.csv")
res_ta_yeast <- c(
"E3_D1_ta_yeast_summary.csv",
"E4_D1_a_j_ta_yeast_summary.csv",
"D2_ta_yeast_summary.csv",
"E4_D1_B_ta_yeast_summary.csv",
"E4_D1_AF_TF_ta_yeast_summary.csv")
name_comp <- c(
"E3_D1",
"E4_D1_a_j",
"D2",
"E4_D1_B",
"E4_D1_AF_TF")
plt <- htmltools::tagList()
for (i in 1:length(name_comp)){
txt <- paste(" ",name_comp[i],sep="")
cat("\n")
cat("##",txt,"\n")
cat("\n")
TC <- read.csv2(paste("../results/",res_TC[i],sep=""))
ta_yeast <- read.csv2(paste("./results/",res_ta_yeast[i],sep=""))
comp <- ta_yeast/TC*100
comp <- melt(comp[,c(2:25)])
p <- ggplot(comp,aes(x = variable, y = value)) +
geom_boxplot() +
xlab("Sample name") +
ylab("% Wheat/Triticum") +
scale_x_discrete(labels = unique(tmp)) +
theme(axis.text.x = element_text(angle = 90)) +
labs(title = name_comp[i])
plt[[i]] <- as.widget(ggplotly(p))
cat(knit_print(ggplotly(p))) #https://stackoverflow.com/questions/48458390/how-to-print-html-interactive-plotly-graphs-within-a-lapply-loop-using-knitr-ren
cat("\n")
}# compare TC - ta/wheat
res_TC <- c(
"results_run1_mqpar_extracts_2gether_D2_combined_txt_proteinGroups.txt_summary.csv")
res_athaliana <- c("D2_athaliana_summary.csv")
name_comp <- c("D2")
plt <- htmltools::tagList()
for (i in 1:length(name_comp)){
txt <- paste(" ",name_comp[i],sep="")
cat("\n")
cat("##",txt,"\n")
cat("\n")
TC <- read.csv2(paste("../results/",res_TC[i],sep=""))
athaliana <- read.csv2(paste("./results/",res_athaliana[i],sep=""))
comp <- athaliana/TC*100
comp <- melt(comp[,c(2:25)])
p <- ggplot(comp,aes(x = variable, y = value)) +
geom_boxplot() +
xlab("Sample name") +
ylab("% AThaliana/Triticum") +
scale_x_discrete(labels = unique(tmp)) +
theme(axis.text.x = element_text(angle = 90)) +
labs(title = name_comp[i])
plt[[i]] <- as.widget(ggplotly(p))
cat(knit_print(ggplotly(p))) #https://stackoverflow.com/questions/48458390/how-to-print-html-interactive-plotly-graphs-within-a-lapply-loop-using-knitr-ren
cat("\n")
}# compare TC - ta/wheat
res_TC <- c(
"results_run1_mqpar_extracts_2gether_D2_combined_txt_proteinGroups.txt_summary.csv")
res_rat <- c("D2_rat_summary.csv")
name_comp <- c("D2")
plt <- htmltools::tagList()
for (i in 1:length(name_comp)){
txt <- paste(" ",name_comp[i],sep="")
cat("\n")
cat("##",txt,"\n")
cat("\n")
TC <- read.csv2(paste("../results/",res_TC[i],sep=""))
rat <- read.csv2(paste("./results/",res_rat[i],sep=""))
comp <- rat/TC*100
comp <- melt(comp[,c(2:25)])
p <- ggplot(comp,aes(x = variable, y = value)) +
geom_boxplot() +
xlab("Sample name") +
ylab("% Rat/Triticum") +
scale_x_discrete(labels = unique(tmp)) +
theme(axis.text.x = element_text(angle = 90)) +
labs(title = name_comp[i])
plt[[i]] <- as.widget(ggplotly(p))
cat(knit_print(ggplotly(p))) #https://stackoverflow.com/questions/48458390/how-to-print-html-interactive-plotly-graphs-within-a-lapply-loop-using-knitr-ren
cat("\n")
}